What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

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The Better Way of Applying Benford’s Law for Fraud Detection

Applying Benford’s Law on large collections of data is an effective way of detecting fraud. In this article, we?ll introduce you to Benford’s Law, talk about how auditors are employing it in fraud detection, and introduce you to a more effective way of integrating it into an IT solution.

Benford’s Law in a nutshell

Benford’s Law states that certain data sets – including certain accounting numbers – exhibit a non-uniform distribution of first digits. Simply put, if you gather all the first digits (e.g. 8 is the first digit of ?814 and 1 is the first digit of ?1768) of all the numbers that make up one of these data sets, the smallest digits will appear more frequently than the larger ones.

That is, according to Benford’s Law,

1 should comprise roughly 30.1% of all first digits;
2 should be 17.6%;
3 should be 12.5%;
4 should be 9.7%, and so on.

Notice that the 1s (ones) occur far more frequently than the rest. Those who are not familiar with Benford’s Law tend to assume that all digits should be distributed uniformly. So when fraudulent individuals tinker with accounting data, they may end up putting in more 9s or 8s than there actually should be.

Once an accounting data set is found to show a large deviation from this distribution, then auditors move in to make a closer inspection.

Benford’s Law spreadsheets and templates

Because Benford’s Law has been proven to be effective in discovering unnaturally-behaving data sets (such as those manipulated by fraudsters), many auditors have created simple software solutions that apply this law. Most of these solutions, owing to the fact that a large majority of accounting departments use spreadsheets, come in the form of spreadsheet templates.

You can easily find free downloadable spreadsheet templates that apply Benford’s Law as well as simple How-To articles that can help you to implement the law on your own existing spreadsheets. Just Google “Benford’s law template” or “Benford’s law spreadsheet”.

I suggest you try out some of them yourself to get a feel on how they work.

The problem with Benford’s Law when used on spreadsheets

There’s actually another reason why I wanted you to try those spreadsheet templates and How-To’s yourself. I wanted you to see how susceptible these solutions are to trivial errors. Whenever you work on these spreadsheet templates – or your own spreadsheets for that matter – when implementing Benford’s Law, you can commit mistakes when copy-pasting values, specifying ranges, entering formulas, and so on.

Furthermore, some of the data might be located in different spreadsheets, which can likewise by found in different departments and have to be emailed for consolidation. The departments who own this data will have to extract the needed data from their own spreadsheets, transfer them to another spreadsheet, and send them to the person in-charge of consolidation.

These activities can introduce errors as well. That’s why we think that, while Benford’s Law can be an effective tool for detecting fraud, spreadsheet-based working environments can taint the entire fraud detection process.

There?s actually a better IT solution where you can use Benford’s Law.

Why a server-based solution works better

In order to apply Benford’s Law more effectively, you need to use it in an environment that implements better controls than what spreadsheets can offer. What we propose is a server-based system.

In a server-based system, your data is placed in a secure database. People who want to input data or access existing data will have to go through access controls such as login procedures. These systems also have features that log access history so that you can trace who accessed which and when.

If Benford’s Law is integrated into such a system, there would be no need for any error-prone copy-pasting activities because all the data is stored in one place. Thus, fraud detection initiatives can be much faster and more reliable.

You can get more information on this site regarding the disadvantages of spreadsheets. We can also tell you more about the advantages of server application solutions.

The Future is Smarter with a Smart Meter

Traditionally, electricity and water meter consumption was measured via analogue meters. Utility billing was based on actual consumption units obtained from the meter by meter readers. This entailed physical visits to the metering point. Lots of challenges came with meter reading; talk of customers feeling their privacy is intruded, meter readers encountering hostile customers, dogs, closed gates. The result was estimated bills that were most often than not very high.

Smart meters can be dubbed as the ?next generation? type of meters. Smart meters send wireless electronic meter readings to one?s energy supplier automatically. There are both gas smart meters and electricity smart meters. Smart meters come with in-home displays, which give someone real-time feedback on their energy usage and the associated cost.

Smart meters communicate meter readings directly to utility companies therefore no one has to come to your home to read your meter; and neither are you required to submit meter readings yourself. This not only reduces costs, but leads to more accurate electricity bills practically eliminating estimated bills. Smart meters signal the end of estimated bills, and the end of overpaying or underpaying for energy.

Whereas a smart meter in itself does not save you money, the add-ons (in-home displays) that come with the smart meters and which give someone real-time feedback on their energy usage helps them to reduce the unnecessary energy use and this ultimately leads to better oversight into how to lower utility bills hence better management of one?s energy use.

In summary, a smart meter is a technology that enables energy consumers to see their energy as they use it, a technology where energy is displayed as it is being used and wireless ratings sent. Adoption of smart meters would mean the end of estimated energy bills.

Smart meters are also promising a smart future where all energy consuming devices can be connected to the internet and centrally controlled using computers or smartphones. This means one is able to switch off lights and other energy consuming devices from a central point, hence make savings and this will enable them to have greater control of their energy use, hence more comfort, convenience and life will be cheaper for all. This is the smarter future we are all looking forward to.

How Small Irish Businesses Avoid the GDPR Sting

Accountants providing chartered accounting services and tax advice are alerting smaller Irish companies to the consequences of the pending General Data Protection Regulation (GDPR). They believe these are going to feel the most pain come 25 May 2018, if they do not implement GDPR by then. We are trying our best to help avoid this situation by providing advice.

How to Kick the GDPR Ball into Play

The Irish Information Commissioner?s Office has produced a toolkit regarding where?s best to start. They suggest beginning with an information security assessment to determine the gaps companies need to close. Once quantified, this leads naturally to a plan of action, and resources needed to fulfil it. Here?s how to go about it:

1. Start by assessing your current ability to identify, assess, and manage threats to customer data security. Have you done anything at all to date? You must be holding some customer information surely, and it is highly likely the GDPR applies to you.

2. Next, review your company?s current customer data security policies. Are they documented and approved, or do new employees discover them sitting next to Nellie? Rate yourself on a scale where ten is successful implementation.

3. Now consider how well you have pinned responsibilities on individuals to implement policies and take the lead on GDPR. The latter should be the business owner, or a board member with clout to make things happen.

4. By now, you should have a grasp of the scale of work ahead of you, remembering the EU deadline is 25 May 2018. If this sounds overwhelming, consider outsourcing to your accountant or a specialist provider.

5. Under the General Data Protection Regulation you have only 72 hours to report a breach of customer data security to the Information Commissioner?s Office. Do you have a quality assurance mechanism to oversee this?

Tangible Things to Bring Your Own People on Board

With all the changes going on, there is a risk of your employees regarding GDPR as ?another management idea going nowhere.? Thus, it is important to incorporate the new EU regulations in staff training, particularly with regard to data security generally. They may fully come on board only once they see tangible signs of progress. You should in any case put the following measures in place unless you already have them:

1. A secure area for your servers and for any paperwork your customers provided. This implies access control on a need-to-know basis to protect the information against loss, damage, and theft.

2. A protocol for storage media and record disposal when you no longer require them or something supersedes them. You are the custodian of other people?s information and they deserve nothing less.

3. Procedures to secure customer data on employee mobile devices and computers: This must extend to work done at home, at consultant sites, and by remote workers.

4. Secure configuration of all existing and new hardware to minimise vulnerability and storage media crashes. These quality assurance measures should extend to removable media and remote backups.

So Is This the Worst of the Pain?

We are at the heart of the matter, although there is more to tell in future articles. You may be almost there, if you already protect your proprietary information. If not, you may have key company information already open to malware.We should welcome the EU General Data Protection Regulation as a notice that it is time to face up to the challenges of data protection and security generally. The age of hacking and malware is upon us. The offender could be a disgruntled employee, or your competition just down the street. It is time to take precautions.

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